Fast Inversion of Eddy Current Testing Data Through a Learning-by-Examples Approach for Robust Crack Localization

Salucci, M. and Anselmi, N. and Oliveri, G. and Massa, A. (2016) Fast Inversion of Eddy Current Testing Data Through a Learning-by-Examples Approach for Robust Crack Localization. Technical Report. University of Trento.

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Abstract

This document presents a new learning-by-example (LBE) technique for the computationally-efficient inversion of eddy current testing (ECT) data in non-destructive testing and evaluation (NDT-NDE) scenarios. More precisely, the developed approach exploits a uniform sampling strategy to build a training set of input/output (I/O) pairs and exploits such information to train a Support Vector Regressor (SVR). During the on-line testing phase, previously-unseen ECT data are given as input to the trained model in order to predict the position of a single narrow crack within a planar conductive structure. Some representative numerical results are shown, in order to preliminarily assess the capabilities of the developed approach when dealing with the presence of a non-negligible amount of noise on test data.

Item Type: Monograph (Technical Report)
Uncontrolled Keywords: Eddy current testing, inverse scattering, nondestructive testing and evaluation, statistical learning, learning-by-examples, support vector regression
Subjects: M Methodologies > M LBE Learning-by-Example Methods
Divisions: University of Trento > Faculty of Telecommunications, Electronics Engineering > Department of Information Engineering and Computer Science > ELEDIA Research Center
URI: http://www.eledia.org/students-reports/id/eprint/712

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